AIMC Topic: Algorithms

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Metric Learning for Multi-atlas based Segmentation of Hippocampus.

Neuroinformatics
Automatic and reliable segmentation of hippocampus from MR brain images is of great importance in studies of neurological diseases, such as epilepsy and Alzheimer's disease. In this paper, we proposed a novel metric learning method to fuse segmentati...

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

JAMA
IMPORTANCE: Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules explicitly. Application of the...

High-throughput time-stretch imaging flow cytometry for multi-class classification of phytoplankton.

Optics express
Time-stretch imaging has been regarded as an attractive technique for high-throughput imaging flow cytometry primarily owing to its real-time, continuous ultrafast operation. Nevertheless, two key challenges remain: (1) sufficiently high time-stretch...

[Research on Control System of an Exoskeleton Upper-limb Rehabilitation Robot].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In order to help the patients with upper-limb disfunction go on rehabilitation training,this paper proposed an upper-limb exoskeleton rehabilitation robot with four degrees of freedom(DOF),and realized two control schemes,i.e.,voice control and elect...

[A Classification Algorithm for Epileptic Electroencephalogram Based on Wavelet Multiscale Analysis and Extreme Learning Machine].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The automatic classification of epileptic electroencephalogram(EEG)is significant in the diagnosis and therapy of epilepsy.A classification algorithm for epileptic EEG based on wavelet multiscale analysis and extreme learning machine(ELM)is proposed ...

Feasibility of Automating Patient Acuity Measurement Using a Machine Learning Algorithm.

Journal of nursing measurement
BACKGROUND AND PURPOSE: One method of determining nurse staffing is to match patient demand for nursing care (patient acuity) with available nursing staff. This pilot study explored the feasibility of automating acuity measurement using a machine lea...

Adaptive Neural Network Control for the Trajectory Tracking of the Furuta Pendulum.

IEEE transactions on cybernetics
The purpose of this paper is to introduce a novel adaptive neural network-based control scheme for the Furuta pendulum, which is a two degree-of-freedom underactuated system. Adaptation laws for the input and output weights are also provided. The pro...

Learning-based 3T brain MRI segmentation with guidance from 7T MRI labeling.

Medical physics
PURPOSE: Segmentation of brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is crucial for brain structural measurement and disease diagnosis. Learning-based segmentation methods depend largel...

A fuzzy neural network sliding mode controller for vibration suppression in robotically assisted minimally invasive surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: It is very important for robotically assisted minimally invasive surgery to achieve a high-precision and smooth motion control. However, the surgical instrument tip will exhibit vibration caused by nonlinear friction and unmodeled dynamic...